recommend_layout

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must convey behavioral traits. It discloses the scope of recommendations (grid system, CSS approach, etc.) but does not explicitly state read-only behavior, output format, or any side effects, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the primary action and then elaborates with specific examples. Every word contributes value; there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple tool with one parameter, no output schema, and no annotations. The description covers purpose, input basis, and the topics of recommendations, which is sufficient for this complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema fully documents the single parameter (content_type) with an enum and description, so the description adds no new parameter semantics. It simply references 'content type' without expanding on the allowed values or formatting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get layout recommendations') and the basis ('based on content type'), and lists the areas covered, making it distinct from generic advice. However, it doesn't explicitly differentiate from sibling tools like get_ia_recommendations, so it lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use it (when you have a content type and need layout advice) but provides no explicit guidance on when not to use it or which alternatives exist. It establishes a clear trigger condition but no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.